Senior Gen AI Platform Engineer

Capital One Group

San Jose (CA)

On-site

USD 215,000 - 246,000

Full time

14 days+

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Job summary

Capital One is seeking an AI Engineer 4 to help build responsible and scalable AI systems. You will partner with engineers, researchers, PMs to deliver AI-powered products that transform how associates work and how customers interact with Capital One.

You will design, deploy, and optimize foundation models, vector databases, and guardrails, while shaping governance, observability, and performance. This role sits in the IFX team, driving long‑term AI strategy across Capital One platforms.

Qualifications

Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies
At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java
Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy
6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)
Experience designing, developing, delivering, and supporting AI services
Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang
Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost
Experience in building agentic AI systems and agentic workflows
Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale
Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules
Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms

Responsibilities

Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products
Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, and observability
Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch
Invent and introduce state-of-the-art foundation model optimization techniques to improve performance, scalability, cost, latency, and throughput
Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment
Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift
Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines
Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met
Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation